This file was created by scanning the printed publication. Errors identified by the software have been corrected; however, some errors may remain. United States Department of Agriculture User's Guide to the Forest Service Intermountain Stand Prognosis Forest and Range Experiment Station Ogden, UT 84401 Model General Technical Report INT-122 April 1982 William R. Wykoff Nicholas L. Crookston Albert R. Stage PREFACE TO THE SECOND PRINTING This reprinting of the User’s Guide to the Prognosis Model describes the Prognosis Model as released in September, 1981 (Version 4.0). Although we will soon release version 5.0, most of the material in this guide will remain applicable to the new version. There will be, however, modifications in the small tree growth models and in the crown-dubbing and crown-changing proce- dures that improve model behavior. These modifica- tions will necessitate revisions of pages 52, 65-67, and 77-80. These revisions, and descriptions of new features, are contained in a supplement to this guide that will be released with the new version. The new features in- clude: —A regeneration establishment component; —SHRUB and COVER extensions; —An event monitor for dynamic activity scheduling; —A classification algorithm used to shorten the tree record list by combining like records; —Expansion of management options. We have endeavored to make changes in such a way that the procedures for using version 4.0 will operate the same way in version 5.0. December 1983 THE AUTHORS RESEARCH SUMMARY WILLIAM R. WYKOFF is a research forester with the The Inland Empire version of the Prognosis Model, a Station’s quantitative analysis of forest management computer program designed to simulate the practices and resources for planning and control development of forest stands, is described. The Inland research work unit at Moscow, Idaho. Mr. Wykoff Empire version is calibrated for eleven tree species received his B.S. in forest management (1970) from the occurring on over 30 habitat types. The individual tree is University of Minnesota, St. Paul, and his M.S. in forest the basic unit of projection and most combinations of management (1975) from Washington State University, species and age classes can be accommodated. Pullman. Since joining the Station in 1974, he has Available thinning options allow considerable latitude worked on the development of tree growth models and for simulation of management strategies. the implementation of these models into the Stand Prognosis Model input consists of a stand inventory, Prognosis system. including a list of sample trees, and a set of specially NICHOLAS L. CROOKSTON is a research associate, formatted instructions that indicate the options College of Forestry, Wildlife and Range Sciences, selected. The output includes distributions of trees per University of Idaho, Moscow. He is currently working on acre, volume per acre, accretion, and mortality by the Canada/U.S. Spruce Budworms Program-West under diameter at breast height and by species and tree value an Intergovernmental Personnel Act agreement between class. In addition, selected sample trees are displayed the Pacific Northwest Station and the University of Idaho. over time along with parameters that describe general He received his B.S. in botany in 1973 from Weber State stand characteristics that might influence tree growth. College and his M.S. in forest resources in 1977 from the The Prognosis Model can be linked to models that University of Idaho. His principal professional activities predict pest outbreaks and the impacts of host-pest have been to incorporate models of dynamics of the interactions. It can also be linked to models that predict mountain pine beetle/lodgepole ecosystem, the Douglas-fir tussock moth/forest ecosystem, and the production of other forest resources. The combined western spruce budworm/forest ecosystem into outputs provides a basis for multiresource planning. extensions to the Stand Prognosis system. Preparation of input, interpretation of output, and ALBERT R. STAGE is principal mensurationist at the model formulation are described. Guidelines are given Forestry Sciences Laboratory, Moscow, Idaho. His for potential uses and limitations. research has included studies of planning methods for forest management, forest inventory techniques, site evaluation, and methods for estimation of stand growth and yield incorporating pest effects. He is Project Leader of a research team studying the problems of developing decision-support systems for forest management in the Northern Rocky Mountains. ACKNOWLEDGMENTS We would like to thank all those people that con- tributed to the preparation of this manual. Dave Hamilton, Bob Monserud, Chuck Hatch, Jim Newberry, Ralph Johnson, and Greg Biging provided excellent technical reviews. The research support staff in Moscow endured both fickleness and chang- ing technology, and processed each revision with more good humor than could be expected. In addi- tion, personnel from National Forest Systems and from industry within the Inland Empire have used the Prognosis Model and early versions of documenta- tion for about 7 years. In this period there has been considerable feedback leading to new options and revisions of the models and documentation. Finally, we would like to thank colleagues at the Forestry Sciences Lab in Moscow and cooperators at the University of Idaho for contributing to the develop- ment and testing of models. Work leading to this publication was funded in part by a USDA Forest Service-sponsored program entitled Canada/United States Spruce Budworms Program. Stand and Tree Characteristics that Can CONTENTS Be Managed ..............................................62 The Height Increment Model.............................65 Page Formulation ...................................................65 Introduction................................................................ 1 Behavior ........................................................68 Yield Data for Forest Planning ............................... 1 Predicting Mortality Rates .................................70 Design Criteria for Development of Prognosis The Diameter-Based Individual Tree Model ..70 Model................................................................ 2 Approach to Normality...................................71 What Management Actions Can Be Represented?4 Approach to Maximum Basal Area................73 The Base Model ................................................. 4 Combining the Mortality Rate Estimates .......75 Extensions and User Supplied Modifications ..... 4 Model Behavior .............................................75 What Data are Required to Describe the Stand? .. 5 Change in Crown Ratio.....................................77 Organization of the Model...................................... 5 Formulation ...................................................77 The Keyword System............................................. 7 Behavior ........................................................79 Simulating Stand Management.................................. 8 Volume Calculations.........................................81 Timing .................................................................... 8 Total Cubic Volume .......................................81 Entering Stand and Tree Data ............................. 10 Board Foot Volume .......................................82 The Sampling Design ....................................... 10 Other Merchantability Standards...................82 Identifying the Stand......................................... 11 Predicted Values...........................................83 Describing the Stand ........................................ 11 Using the Prognosis Model as a Component of a Sample Tree Data ............................................ 13 Planning System.................................................84 Record Format..................................................19 Resource Allocation and Harvest Scheduling ......84 Species Codes ................................................. 19 Inventory Considerations..................................84 Interpreting Increment Data.............................. 20 Pest Impacts.....................................................85 Stand Management Options ................................ 21 Multiresource Allocation Problems....................86 General Rules................................................... 21 Stand Prescription................................................86 Cutting Efficiency.......................................... 21 Regeneration Systems......................................86 Date Specification......................................... 21 Economic Evaluation of Prescriptions...............86 Specifying Minimum Acceptable Harvests.... 21 Summary..................................................................87 Modifying Volume Calculations ........................ 22 Publications Cited ....................................................87 Requesting Removal of Specific Trees or Appendix A: Representing Differences Between Classes of Trees............................................. 24 the Real World and the Model ..........................89 Prescription Thinning .................................... 24 Introduction...........................................................89 Diameter Limit Thinnings .............................. 24 Calculation of Scale Factors.................................90 Controlling Stand Density................................. 26 Random